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feat: add blas/ext/base/ndarray/ctriu
PR-URL: #14104 Reviewed-by: Athan Reines <kgryte@gmail.com> Signed-off-by: Kaustubh Patange <kaustubh.mp007@gmail.com>
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‎lib/node_modules/@stdlib/blas/ext/base/ndarray/ctriu/README.md‎

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<!--
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@license Apache-2.0
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Copyright (c) 2026 The Stdlib Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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-->
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# ctriu
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> Copy the upper triangular part of a single-precision complex floating-point matrix `A` to another matrix `B`.
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<section class="intro">
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</section>
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<!-- /.intro -->
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<section class="usage">
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## Usage
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```javascript
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var ctriu = require( '@stdlib/blas/ext/base/ndarray/ctriu' );
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```
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#### ctriu( arrays )
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Copies the upper triangular part of a single-precision complex floating-point matrix `A` to another matrix `B`.
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<!-- eslint-disable max-len -->
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```javascript
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var Complex64Matrix = require( '@stdlib/ndarray/matrix/complex64' );
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var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
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var A = new Complex64Matrix( [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ] );
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var B = new Complex64Matrix( [ [ 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0 ] ] );
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var k = scalar2ndarray( 0, {
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'dtype': 'generic'
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});
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var out = ctriu( [ A, B, k ] );
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// returns <ndarray>[ [ <Complex64>[ 1.0, 2.0 ], <Complex64>[ 3.0, 4.0 ] ], [ <Complex64>[ 0.0, 0.0 ], <Complex64>[ 7.0, 8.0 ] ] ]
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var bool = ( out === B );
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// returns true
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```
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The function has the following parameters:
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- **arrays**: array-like object containing the following ndarrays:
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- a two-dimensional input ndarray corresponding to `A`.
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- a two-dimensional output ndarray corresponding to `B`.
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- a zero-dimensional ndarray specifying the diagonal below which to ignore. A value equal to zero refers to the main diagonal, greater than zero refers to a diagonal above the main diagonal, and less than zero refers to a diagonal below the main diagonal.
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</section>
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<!-- /.usage -->
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<section class="notes">
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## Notes
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- Elements outside of the copied region are left unchanged.
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</section>
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<!-- /.notes -->
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<section class="examples">
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## Examples
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<!-- eslint no-undef: "error" -->
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<!-- eslint-disable max-len -->
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```javascript
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var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var Complex64Matrix = require( '@stdlib/ndarray/matrix/complex64' );
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var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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var ctriu = require( '@stdlib/blas/ext/base/ndarray/ctriu' );
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var opts = {
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'dtype': 'float32'
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};
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var A = new Complex64Matrix( discreteUniform( 5*5*2, -50, 50, opts ).buffer, 0, 5, 5 );
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console.log( ndarray2array( A ) );
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var B = new Complex64Matrix( discreteUniform( 5*5*2, -50, 50, opts ).buffer, 0, 5, 5 );
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console.log( ndarray2array( B ) );
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var k = scalar2ndarray( 0, {
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'dtype': 'generic'
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});
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var out = ctriu( [ A, B, k ] );
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console.log( ndarray2array( out ) );
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```
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</section>
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<!-- /.examples -->
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<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
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<section class="related">
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</section>
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<!-- /.related -->
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<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
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<section class="links">
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</section>
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<!-- /.links -->

‎lib/node_modules/@stdlib/blas/ext/base/ndarray/ctriu/benchmark/benchmark.js‎

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2026 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var bench = require( '@stdlib/bench' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var Complex64Matrix = require( '@stdlib/ndarray/matrix/complex64' );
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var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
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var realf = require( '@stdlib/complex/float32/real' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var format = require( '@stdlib/string/format' );
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var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
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var pkg = require( './../package.json' ).name;
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var ctriu = require( './../lib' );
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// VARIABLES //
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var options = {
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'dtype': 'float32'
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};
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// FUNCTIONS //
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/**
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* Creates a benchmark function.
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*
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* @private
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* @param {PositiveInteger} len - array length
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
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var abuf;
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var bbuf;
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var A;
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var B;
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var k;
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abuf = uniform( len*len*2, -100.0, 100.0, options );
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bbuf = uniform( len*len*2, -100.0, 100.0, options );
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A = new Complex64Matrix( abuf.buffer, 0, len, len );
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B = new Complex64Matrix( bbuf.buffer, 0, len, len );
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k = scalar2ndarray( 0, {
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'dtype': 'generic'
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});
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return benchmark;
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/**
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* Benchmark function.
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*
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* @private
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* @param {Benchmark} b - benchmark instance
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*/
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function benchmark( b ) {
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var out;
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var i;
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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out = ctriu( [ A, B, k ] );
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if ( typeof out !== 'object' ) {
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b.fail( 'should return an ndarray' );
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}
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}
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b.toc();
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if ( isnanf( realf( out.get( i%len, i%len ) ) ) ) {
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b.fail( 'should return an ndarray' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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}
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}
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// MAIN //
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/**
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* Main execution sequence.
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*
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* @private
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*/
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function main() {
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var len;
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var min;
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var max;
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var f;
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var i;
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min = 1; // 10^min
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max = 3; // 10^max
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for ( i = min; i <= max; i++ ) {
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len = pow( 10, i );
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f = createBenchmark( len );
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bench( format( '%s:len=%d', pkg, len ), f );
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}
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}
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main();

‎lib/node_modules/@stdlib/blas/ext/base/ndarray/ctriu/docs/repl.txt‎

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{{alias}}( arrays )
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Copies the upper triangular part of a single-precision complex floating-
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point matrix `A` to another matrix `B`.
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The diagonal parameter `k` specifies the diagonal below which to ignore. A
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value of `k = 0` refers to the main diagonal, `k > 0` refers to a diagonal
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above the main diagonal, and `k < 0` refers to a diagonal below the main
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diagonal.
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Parameters
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----------
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arrays: ArrayLikeObject<ndarray>
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Array-like object containing the following ndarrays:
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- a two-dimensional input ndarray corresponding to `A`.
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- a two-dimensional output ndarray corresponding to `B`.
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- a zero-dimensional ndarray specifying the diagonal below which to
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ignore.
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Returns
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-------
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out: ndarray
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Output ndarray.
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Examples
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--------
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> var abuf = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];
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> var A = new {{alias:@stdlib/ndarray/matrix/complex64}}( abuf );
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> var bbuf = [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ];
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> var B = new {{alias:@stdlib/ndarray/matrix/complex64}}( bbuf );
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> var k = {{alias:@stdlib/ndarray/from-scalar}}( 0, { 'dtype': 'generic' } );
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> {{alias}}( [ A, B, k ] );
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> B
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<ndarray>[ [ <Complex64>[ 1.0, 2.0 ] ], [ <Complex64>[ 0.0, 0.0 ] ] ]
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See Also
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--------
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‎lib/node_modules/@stdlib/blas/ext/base/ndarray/ctriu/docs/types/index.d.ts‎

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/*
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* @license Apache-2.0
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*
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* Copyright (c) 2026 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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// TypeScript Version: 4.1
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/// <reference types="@stdlib/types"/>
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import { complex64ndarray, typedndarray } from '@stdlib/types/ndarray';
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/**
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* Copies the upper triangular part of a single-precision complex floating-point matrix `A` to another matrix `B`.
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*
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* ## Notes
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*
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* - The function expects the following ndarrays:
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*
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* - a two-dimensional input ndarray corresponding to `A`.
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* - a two-dimensional output ndarray corresponding to `B`.
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* - a zero-dimensional ndarray specifying the diagonal below which to ignore.
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*
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* @param arrays - array-like object containing ndarrays
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* @returns output ndarray
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*
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* @example
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* var Complex64Matrix = require( '@stdlib/ndarray/matrix/complex64' );
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* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
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*
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* var A = new Complex64Matrix( [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ] );
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* var B = new Complex64Matrix( [ [ 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0 ] ] );
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*
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* var k = scalar2ndarray( 0, {
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* 'dtype': 'generic'
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* });
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*
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* var out = ctriu( [ A, B, k ] );
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* // returns <ndarray>[ [ <Complex64>[ 1.0, 2.0 ], <Complex64>[ 3.0, 4.0 ] ], [ <Complex64>[ 0.0, 0.0 ], <Complex64>[ 7.0, 8.0 ] ] ]
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*
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* var bool = ( out === B );
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* // returns true
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*/
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declare function ctriu( arrays: [ complex64ndarray, complex64ndarray, typedndarray<number> ] ): complex64ndarray;
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// EXPORTS //
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export = ctriu;

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